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transition of quality advisors in the non-formal education sector towards their new exclusive role as quality facilitators. The objectives are to systematically document and analyse organisational and
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state-of-the art methods. Extensive experience in Heterogeneous Catalysis research area as evidenced through peer-reviewed journal publications. Applicants are encouraged to add their three best
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of results in scientific journals Requirements PhD in Physics, Engineering, Economics, Environmental Sciences, Mathematics, System Sciences or a related field training in formal, quantitative methods
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to develop innovative methods and actionable tools for detecting, analyzing, and preventing vulnerabilities in supply chain systems, leveraging state-of-the-art AI and ML techniques to improve overall security
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experience in machine learning methods, tools, and platforms. Proficiency in Python, with demonstrated software development experience. Hands-on experience in MLOps, including the design and deployment
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considered an asset Training and experience in quantitative empirical methods Good command of multivariate and complex statistical methods International publications in peer-reviewed journals and / or book
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, Luxembourgish and / or French will be considered an asset Interest in empirical social research, excellent command of quantitative and / or qualitative empirical methods; openness to mixed methods research
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Analyze and assess risks of de-anonymization, including researching current de-anonymization strategies Investigate synthetic data generation methods and their utility Deploying and benchmarking the above
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experimental methods, analyse data and present results within the framework of the project;Write progress reports, participate in group meetings, publish research findings in scientific journals and present
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, work together and exchange knowledge, which promotes a dynamic and open culture. Qualifications - This is how the position is assessed: You need to have met the following two formal requirements by